What if the future of healthcare depends less on treating disease and more on detecting it years before symptoms appear? In this DLD Health talk, Nobel laureate Ferenc Krausz argues that AI can revolutionize medicine – provided that it is trained on better data: not data from patients who are already sick, but repeated, affordable measurements from people while they are still healthy.
“The bad news is that unfortunately the available data are just not good enough for shaping the future of healthcare, which is supposed to be preventive”, Krausz notes – simply because health data is typically collected “at a symptomatic stage of the disease”, meaning when patients are already undergoing treatment.
To address the problem, Krausz helped to launch Protecting.Health, a global initiative that aims to deliver “precision prevention” by collecting individual health data of millions of people, repeatedly, to flag disease years before symptoms appear.
Watch the video to explore this talk in detail.
